1985
DOI: 10.1145/2786.2793
|View full text |Cite
|
Sign up to set email alerts
|

Amortized efficiency of list update and paging rules

Abstract: In this article we study the amortized efficiency of the “move-to-front” and similar rules for dynamically maintaining a linear list. Under the assumption that accessing the ith element from the front of the list takes θ(i) time, we show that move-to-front is within a constant factor of optimum among a wide class of list maintenance rules. Other natural heuristics, such as the transpose and frequency count rules, do not share this property. We generalize our results to show that move-to-front is within a const… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
858
1
4

Year Published

1999
1999
2015
2015

Publication Types

Select...
6
3
1

Relationship

0
10

Authors

Journals

citations
Cited by 1,789 publications
(864 citation statements)
references
References 2 publications
1
858
1
4
Order By: Relevance
“…Thus, these algorithms are designed to operate in scenarios where the entire input is not known at the outset, and new pieces of the input should be incorporated as they become available. The distinctive feature of the online algorithm approach is the method used to evaluate an algorithm's performance, which is called competitive analysis (Sleator and Tarjan, 1985). In competitive analysis, the performance of an online algorithm is compared to the performance of a corresponding offline algorithm (i.e., an algorithm that has a priori knowledge of the entire input) in the worst-case scenario.…”
Section: Online Algorithmsmentioning
confidence: 99%
“…Thus, these algorithms are designed to operate in scenarios where the entire input is not known at the outset, and new pieces of the input should be incorporated as they become available. The distinctive feature of the online algorithm approach is the method used to evaluate an algorithm's performance, which is called competitive analysis (Sleator and Tarjan, 1985). In competitive analysis, the performance of an online algorithm is compared to the performance of a corresponding offline algorithm (i.e., an algorithm that has a priori knowledge of the entire input) in the worst-case scenario.…”
Section: Online Algorithmsmentioning
confidence: 99%
“…As a measure of efficiency, we adopt the competitive ratio [9], which has been widely used in analyzing the performance of online algorithms. Let σ = σ 1 · · · σ L be a request sequence of the adversary, where σ i = (v i , w i ) is the request in the i-th phase.…”
Section: Initializationmentioning
confidence: 99%
“…The competitive ratio is the ratio of the solution computed by the online algorithm and the cost of the optimal offline solution. This approach is called competitive analysis; it was introduced by Sleator and Tarjan in 1985 [11]. We now formally define the above concepts, i.e., online problems (in this paper, we only consider the objective to minimize some cost), online algorithms, and their competitive ratio.…”
Section: Introductionmentioning
confidence: 99%